[Bug]: Qwen3-VL shows inconsistent accuracy between enabled and disabled graph modes on VLLM0.20.2

[Seren-hao]

Your current environment

vllm version: 0.20.2

🐛 Describe the bug

vllm version: 0.20.2

In the launch script, +trainer.val_only=True and trainer.val_before_train=True were enabled to evaluate the inference. The evaluation scores on the same dataset (geo3k) were 0.49 and 0.42, respectively.

    trainer.project_name='verl_grpo_example_geo3k' \
    trainer.experiment_name='qwen3_vl_30b_megatron' \
    trainer.n_gpus_per_node=16 \
    trainer.device=npu \
    trainer.nnodes=1 \
    +trainer.val_only=True \
    trainer.val_before_train=True \
    trainer.resume_mode=disable \
    trainer.default_local_dir='/home/l00937981/qwen3vl_vllm0202/ckpt' \
    trainer.save_freq=5 \
    trainer.test_freq=5 \

The training accuracy curves are also completely misaligned. In particular, there is a significant discrepancy in the rollout_probs_diff_mean metric, which averages 0.02 with graph mode enabled, but drops to 0.007 when graph mode is disabled.

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[WangX0111]

Could this discrepancy be caused by the different attention operators used in NPU Graph Mode?